Evidence mapPaperPMID 40574088Full record

ReviewPharmaceutics2025

Revolutionizing Diabetes Management Through Nanotechnology-Driven Smart Systems.

Aayush Kaushal, Aanchal Musafir, Gourav Sharma, Shital Rani, Rajat Kumar Singh, Akhilesh Kumar, Sanjay Kumar Bhadada, Ravi Pratap Barnwal, Gurpal Singh

Abstract readReview
In one paragraph

Review in Pharmaceutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Aayush KaushalUniversity Institute of Pharmaceutical Sciences, Panjab University, Chandigarh 160014, India.
Aanchal MusafirUniversity Institute of Pharmaceutical Sciences, Panjab University, Chandigarh 160014, India.
Gourav SharmaUniversity Institute of Pharmaceutical Sciences, Panjab University, Chandigarh 160014, India.
Shital RaniDepartment of Biophysics, Panjab University, Chandigarh 160014, India.
Rajat Kumar SinghDepartment of Biophysics, Panjab University, Chandigarh 160014, India.
Akhilesh KumarDivision of Medicine, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, India.
Sanjay Kumar BhadadaDepartment of Endocrinology, PGIMER, Chandigarh 160012, India.
Ravi Pratap BarnwalDepartment of Biophysics, Panjab University, Chandigarh 160014, India.ORCID 0000-0003-3156-5357
Gurpal SinghUniversity Institute of Pharmaceutical Sciences, Panjab University, Chandigarh 160014, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes is a global health challenge, and while current treatments offer relief, they often fall short in achieving optimal control and long-term outcomes. Nanotechnology offers a groundbreaking approach to diabetes management by leveraging materials at the nanoscale to improve drug delivery, glucose monitoring, and therapeutic precision. Early advancements focused on enhancing insulin delivery through smart nanosystems such as tiny capsules that gradually release insulin, helping prevent dangerous drops in blood sugar. Simultaneously, the development of nanosensors has revolutionised glucose monitoring, offering real-time, continuous data that empowers individuals to manage their condition more effectively. Beyond insulin delivery and monitoring, nanotechnology enables targeted drug delivery systems that allow therapeutic agents to reach specific tissues, boosting efficacy while minimising side effects. Tools like microneedles, carbon nanomaterials, and quantum dots have made treatment less invasive and more patient-friendly. The integration of artificial intelligence (AI) with nanotechnology marks a new frontier in personalised care. AI algorithms can analyse individual patient data to adjust insulin doses and predict glucose fluctuations, paving the way for more responsive, customised treatment plans. As these technologies advance, safety remains a key concern. Rigorous research is underway to ensure the biocompatibility and long-term safety of these novel materials. The future of diabetes care lies in the convergence of nanotechnology and AI, offering personalised, data-driven strategies that address the limitations of conventional approaches. This review explores current progress, persistent challenges, and the transformative potential of nanotechnology in reshaping diabetes diagnosis and treatment and improving patient quality of life.

Indexed as

AI in diabetes managementcarbon nanomaterialscontinuous glucose monitoring (CGM)diabetes mellitusdiabetic wound healingdrug delivery systemselectrochemical biosensorsglucose biosensorsglucose monitoringinsulin deliverymicroneedlesnanofibersnanomedicinenanotechnologynon-invasive monitoringpolymeric nanoparticlesquantum dots (QDs)smart nanocarrierswearable biosensors

Identifiers

PMID40574088
PMCPMC12196884

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.